Cellular Wave Computing in Nanoscale via Million Processor Chips



A bifurcation is emerging in computer science and engineering due to the sudden emergence of many-core or even kilo-processor chips on the market. Due to the physical limitations, in CMOS technologies below 65 nm, a drastic power dissipation limit, a major signal propagation speed and distance limit, and a distributed character of the circuit elements are forcing new architectures. As a result, locality, the local connectedness becomes a prevailing property, the cellular, i.e., mainly locally connected processor arrays are becoming the norm, and the cellular wave dynamics can produce unique and practical effects.

In this new world, new principles are needed and new design methodologies. Luckily, the 15 years of research and development in cellular wave computing and CNN technology, we have aquired skills that help establishing some principles and techniques that might lead toward a new computer science and technology in designing mega-processor systems from kilo-processor chips.

In this chapter, we review the architectural development from standard CNN dynamics to the Cellular Wave Computer, showing several practical implementations, introduce the basic concepts of the Virtual Cellular Machine, present a new kind of implementation combining spatial-temporal algorithms with physics, give some architectural principles for non-CMOS implementations, and comment on biological relevance.


Image Flow Black Pixel Disjunctive Normal Form Processor Array Natural Noise 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The supports of the Office of Naval Research, the Future and Emerging Technology program of the EU, the Computer and Automation Research Institute of the Hungarian Academy of Sciences, the Hungarian National Research Fund (OTKA), the Pázmány P. Catholic University, Budapest, the University of California at Berkeley, and the University of Notre Dame are gratefully acknowledged.


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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Tamás Roska
    • 1
  • Laszlo Belady
    • 2
  • Maria Ercsey-Ravasz
    • 3
  1. 1.Computer and Automation Institute of the Hungarian Academy of Sciences and the Faculty of Information Technology of the Pázmány UniversityBudapestHungary
  2. 2.Eutecus Inc.BerkeleyU.S.A.
  3. 3.University of Notre DameNotre DameU.S.A.

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